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| Auteurs principaux: | , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2505.12583 |
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| _version_ | 1866913866446798848 |
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| author | Kojima, Takeshi Zhu, Yaonan Iwasawa, Yusuke Kitamura, Toshinori Yan, Gang Morikuni, Shu Takanami, Ryosuke Solano, Alfredo Matsushima, Tatsuya Murakami, Akiko Matsuo, Yutaka |
| author_facet | Kojima, Takeshi Zhu, Yaonan Iwasawa, Yusuke Kitamura, Toshinori Yan, Gang Morikuni, Shu Takanami, Ryosuke Solano, Alfredo Matsushima, Tatsuya Murakami, Akiko Matsuo, Yutaka |
| contents | Recent Foundation Model-enabled robotics (FMRs) display greatly improved general-purpose skills, enabling more adaptable automation than conventional robotics. Their ability to handle diverse tasks thus creates new opportunities to replace human labor. However, unlike general foundation models, FMRs interact with the physical world, where their actions directly affect the safety of humans and surrounding objects, requiring careful deployment and control. Based on this proposition, our survey comprehensively summarizes robot control approaches to mitigate physical risks by covering all the lifespan of FMRs ranging from pre-deployment to post-accident stage. Specifically, we broadly divide the timeline into the following three phases: (1) pre-deployment phase, (2) pre-incident phase, and (3) post-incident phase. Throughout this survey, we find that there is much room to study (i) pre-incident risk mitigation strategies, (ii) research that assumes physical interaction with humans, and (iii) essential issues of foundation models themselves. We hope that this survey will be a milestone in providing a high-resolution analysis of the physical risks of FMRs and their control, contributing to the realization of a good human-robot relationship. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_12583 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Comprehensive Survey on Physical Risk Control in the Era of Foundation Model-enabled Robotics Kojima, Takeshi Zhu, Yaonan Iwasawa, Yusuke Kitamura, Toshinori Yan, Gang Morikuni, Shu Takanami, Ryosuke Solano, Alfredo Matsushima, Tatsuya Murakami, Akiko Matsuo, Yutaka Robotics Artificial Intelligence Machine Learning Recent Foundation Model-enabled robotics (FMRs) display greatly improved general-purpose skills, enabling more adaptable automation than conventional robotics. Their ability to handle diverse tasks thus creates new opportunities to replace human labor. However, unlike general foundation models, FMRs interact with the physical world, where their actions directly affect the safety of humans and surrounding objects, requiring careful deployment and control. Based on this proposition, our survey comprehensively summarizes robot control approaches to mitigate physical risks by covering all the lifespan of FMRs ranging from pre-deployment to post-accident stage. Specifically, we broadly divide the timeline into the following three phases: (1) pre-deployment phase, (2) pre-incident phase, and (3) post-incident phase. Throughout this survey, we find that there is much room to study (i) pre-incident risk mitigation strategies, (ii) research that assumes physical interaction with humans, and (iii) essential issues of foundation models themselves. We hope that this survey will be a milestone in providing a high-resolution analysis of the physical risks of FMRs and their control, contributing to the realization of a good human-robot relationship. |
| title | A Comprehensive Survey on Physical Risk Control in the Era of Foundation Model-enabled Robotics |
| topic | Robotics Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2505.12583 |